23 Jun
22 Jun

In the Press: How fintechs are using AI to process customer feedback

Find us at Banking Sector Magazine talking about ‘How fintechs are using AI to process customer feedback.’

More banks are turning to practical AI to rapidly analyse customer conversations for sentiment and emotional intent to get the insight and automation they need to transform their customer service and operations.

Essentially, AI-based technologies remove the need for complex models and instead, analyse information in real-time and update themselves (with minimal human input). This allows the results to be far quicker and more accurate than traditional methods, such as instating teams of analysts or older machine learning methods.

In the article with Banking Sector, we look at five ways in which banks are using AI to process their customer feedback more effectively.

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23 Apr

Watch again: How leading organisations are responding to the impact of coronavirus

Last week our partners at Ember hosted a webinar that shared examples and learnings from the market on how organisations are adapting their operating model during the current crisis, establishing new ways of working, innovating by using digital and automation technologies, and critically, preparing to operate differently for an as-yet-uncertain future.

You can now watch the recorded webinar using the following link and password:

https://vimeo.com/407515308

Password: adapt123

Enjoy and stay safe.

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01 Apr

Webinar: How leading organisations are responding to the impact of coronavirus

 

WEBINAR: 14:00pm – 14:40pm     |     Thursday 9th April      |   REGISTER HERE

 

The coronavirus outbreak has had an unprecedented impact on organisations, their operations and the management of workforces. With some needing to respond to substantially increased demand and others facing a situation where customer demand has virtually stopped, the extremes of the impact are clear. When combined with the natural uncertainty and anxiety that everyone will have, this has created a scenario that has never been faced in modern times.

Our partner Ember is seeing this unfold and helping support our customers respond to this crisis. We have been inspired by the effort, innovation, commitment and resilience being shown as teams rally around, often for the first time, to get things done; and in response, adapt their support for customers and their teams.

This event is designed to share our experience, which we are seeing across the market. The webinar will be hosted Mike Havard, Chairman of Ember Group and Carolyn Blunt, Director of Learning Solutions who will share examples and learnings from the market on how organisations are adapting their operating model, establishing new ways of working, innovating by using digital and automation technologies, and critically, preparing to operate differently for an as-yet-uncertain future.

We’d love to have you join us in this event and share your own experiences, as this is one of the ways we can all help each other to get through this crisis. The webinar is being held on 9th April at 2pm (GMT), and all you need to do to register is click on the link below.

JOIN THE WEBINAR

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25 Mar

Warwick Analytics launch Zendesk app for automated classification of tickets

Warwick Analytics has launched an app for Zendesk users that installs directly into the platform where it applies automated classification and tagging for support tickets.

The ‘PrediCX’ app can be downloaded from the Zendesk app store.

Through the app Warwick Analytics will apply its Machine Learning-based interaction analytics to unstructured customer data within support tickets whether they come via chat, web forms or email.

The full topics, sentiment and emotional intents of the contact will be automatically analysed and classified, accurately in near real time. This saves the call center or helpdesk having to classify each ticket manually, or using keyword classification which can be inaccurate.

Users will be able to set alerts for the early warnings of issues and complaints so they can be triaged, and where necessary prioritised and escalated fast. This means that an issue that could otherwise become a brand-affecting event, such as a serious customer issue that might otherwise end up on social media, can be dealt with by the right person at the right time.

The PrediCX app also features Multi-label Capability which means it can identify and classify multiple topics, sentiments and intents within a single piece of customer feedback, something that is often missed with human or generic ML classification.

Dan Somers, CEO at Warwick Analytics adds: “With the new app Zendesk users can analyse customer interactions across all customer touch-points, and use the insight to define and optimise support strategies. Helpdesks will be able to improve the speed of resolution, provide more relevant responses and streamline their chat optimisation process.”

Lee Mostari, Director of Insights & Analytics at Ember, a partner of Warwick Analytics, adds: “The world is becoming faster-moving with consumers demanding quicker service and more transparency than ever before. This Zendesk App enables brands to deal with the right queries in the right order and optimise the customer experience. Not only does this optimise customer operations, but it helps to protect and maintain the brand as well to enhance customer advocates and minimise customer detraction which from digital customers can both quickly amplify on social media.”

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06 Mar

Omni-channel Series: SUMMARY – 6 quick fire ways to offer an omni-channel experience

In this Omni-channel Series we’ve looked at why you should adopt an omni-channel customer experience, the top use cases for an omni-channel experience, what an omni-channel model should look like and why your omni-channel might be failing. In this final blog of the series, we summarise the quick fire ways to implement an effective omni-channel experience:

  1. Analyse customer frustrations and the failure within each channel e.g. containment and the root cause of switch. That’s going to give you the right insight to reduce friction.
  2. Identify the insights into what customers are trying to achieve in the channel and help build that roadmap to change. So if customers are telling you they’re trying to do certain transactions in a certain way, capitalize on that to get the best bang for your buck from the digital roadmap.
  3. Prioritize changes that deliver both an improved CX as well as reducing operational costs. You’ll get a quicker payback to fund more change.
  4. Work to reduce the channel silos and reduce customer friction. A typical target operating model to achieve this is between one and three years so this will take time but start none the less and you will realize benefits and reduce channel friction as you go through that journey.
  5. Aim for an omni-channel experience in which every customer knows what channel to use for what transaction and every interaction is handled correctly first time, Again this will take time and may not by 100pc achievable but let’s make inroads to try to move to that space.
  6. Be prepared to be overwhelmed for a short period of time – by the data and by the possibilities. Work with a partner who can help to make a quick difference, because otherwise PRCs will just become science experiments and a reason to not do things. Making a small thing successful to start with is always better than anything else.
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04 Mar

Download your free copy of Supermarket Social Christmas Edition

Welcome to the latest edition of the Supermarket Social report series, focussing on the 2019 Christmas period. The analysis within the report is brought to you in conjunction with our partners Solutions for Retail Brands (S4RB)

In this edition we discuss some of the trends uncovered from Twitter during the Christmas 2019 trading period (15th November 2019 – 15th January 2020) pertaining to the big six UK Grocery retailers : Asda, Coop, Sainsburys, Morrisons, Tesco and Waitrose.

Using the Warwick Analytics PrediCX engine, Twitter chatter mentioning the above retailers was labelled and categorised, enabling S4RB to apply their Own Brand industry expertise to identify several key themes in the market including: Meat-free Meat-free products continue to grow in popularity, Christmas-online The Christmas online shop is a key battleground and Tracking Tracking competitors can avoid product incidents.

Download your free copy of Supermarket Social Christmas Edition here.

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18 Feb

Omni-channel Series #4: Why your omni-channel experience might be failing

 

In the 4th of our Omni-channel Series of blogs we look at why your omni-channel experience might be failing. It’s likely that you will be receiving customer feedback through a growing number of different channels such as surveys, customer conversations from interactions, or insights from customer actions – or how Garter describe it: Direct, Indirect and Inferred customer feedback. But as you try and provide a customer experience that operates consistently and efficiently across all channels there are some common barriers that might be getting in the way of success.

No empowered CX leader

Only 30% of organisations have an executive on the board representing CX. We think this is very low as we believe not having a single owner has a high risk of creating channel silos.

For example, we quite often see web self-service being owned by somebody different to telephony and customer service, with different agendas and different objectives. And that can lead to some friction.

Paradoxically, 9 out of 10 organisations see customer experience as a competitive differentiator. But if only 30% have an executive responsible for CX on the board, how are they going to deliver great customer experience with a silo channel approach? There’s certainly a high risk of failure there.

Furthermore, probably less than half of the 30% may not be empowered CX leaders. In other words, even if there’s someone responsible for CX, actually having the capability to affect cross functional change is easier said than done – some boards are just more receptive to empowering individuals. Consider whether your CX leader is as empowered as they could be.

Channel failure driving interactions

We found that 40-70% of interactions were driven from some sort of failure in the originating channel. In particular, 25-40% was driven from web self-service. This means customers have tried a cheap service channel in the first instance and then ended up switching to a more expensive channel to get their query resolved…that’s a massive amount of unnecessary demand and cost.

Although many organisations acting on the drivers of failure demand have delivered operational savings of around 11-20% this is still way below expectations and there is plenty of opportunity to improve, particularly if up to 70% of contact is waste!

Channels are not connected

Only 8.4% of organisations have every channel connected. For the other 92%, this is inevitably going to lead to friction because they’re not aligned. That runs the risk of some customer dissatisfaction and so we’re seeing an increasing number of organisations who are actively working towards a truly connected channel strategy.

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04 Feb

Omni-channel Series #3: What does a perfect Omni-channel model look like?

So, in our earlier articles in this series we looked at why you should adopt an omni-channel customer experience and 5 strong use cases for omni-channel analytics. Now let’s take a look at what an effective omni-channel operating model should and shouldn’t look like.

Let’s start with what an omni-channel experience SHOULDN’T look like, most likely commonplace in the majority of organisations. We call it the hourglass shape and hopefully you can see why (see fig below).

What we see is a fat self-serve at the bottom which is good as it’s the cheapest mode. Chatbots are being used to field a lot this section off. But then live chat is not being used as strategically as it could be as the next level up. All too often customers end up coming back to use Voice as a channel, often through channel failure or switching which is expensive and bad for customer experience. In this model everything can be seen as trying to deflect from voice and First-Call resolution (FCR), as opposed to being a joined up strategy.

Even though Voice is the most complex and the most expensive channel, typically 70% of traffic is exactly that. Ideally Voice should deal mostly with the most complex queries.

Now let’s look at the utopia, how your omni-channel experience should look like.


– You would have the biggest number of transactions going through self service
– Then information requests or simple questions would be handled via a chatbot so no need to have an expensive agent conversation – and its accurate and optimised!
– You would offer a live chat provision to help with operational contact management (so concurrent customer conversations) where there is some complexity so requires an assisted channel but is handled efficiently
– And finally, traditional telephony agent conversations. These would be customers seeking guidance on what product to buy or maybe highly emotional conversations requiring a human interaction

In this utopia state, every customer knows what channel to use for what transaction, every interaction is handled correctly first time, there is no failure and the world is lovely.

OK, so we now know the utopian vision that we should strive for but the reality is perhaps something like this, which we call more of a target state.
There will be an element of failure, represented in red, but this would be significantly reduced in a more joined up approach.

The start point for many organisations is essentially delivering the different channel options. And we know, a lot of organizations are still yet to go on the chatbot journey, and some don’t have live chat.

The aim is a more joined up approach, understanding what is failing within each channel, and having the sort of the insights and the analytics to help improve and reduce that non first contact resolution. This is a great step forward and what we should be striving to achieve.

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04 Feb

Omni-channel Series #3: What does a perfect Omni-channel model look like?

So, in our earlier articles in this series we looked at why you should adopt an omni-channel customer experience and 5 strong use cases for omni-channel analytics. Now let’s take a look at what an effective omni-channel operating model should and shouldn’t look like.

Let’s start with what an omni-channel experience SHOULDN’T look like, most likely commonplace in the majority of organisations. We call it the hourglass shape and hopefully you can see why (see fig below).

What we see is a fat self-serve at the bottom which is good as it’s the cheapest mode. Chatbots are being used to field a lot this section off. But then live chat is not being used as strategically as it could be as the next level up. All too often customers end up coming back to use Voice as a channel, often through channel failure or switching which is expensive and bad for customer experience. In this model everything can be seen as trying to deflect from voice and First-Call resolution (FCR), as opposed to being a joined up strategy.

Even though Voice is the most complex and the most expensive channel, typically 70% of traffic is exactly that. Ideally Voice should deal mostly with the most complex queries.

Now let’s look at the utopia, how your omni-channel experience should look like.


  • – You would have the biggest number of transactions going through self service
    – Then information requests or simple questions would be handled via a chatbot so no need to have an expensive agent conversation – and its accurate and optimised!
    – You would offer a live chat provision to help with operational contact management (so concurrent customer conversations) where there is some complexity so requires an assisted channel but is handled efficiently
    – And finally, traditional telephony agent conversations. These would be customers seeking guidance on what product to buy or maybe highly emotional conversations requiring a human interaction

In this utopia state, every customer knows what channel to use for what transaction, every interaction is handled correctly first time, there is no failure and the world is lovely.

OK, so we now know the utopian vision that we should strive for but the reality is perhaps something like this, which we call more of a target state.
There will be an element of failure, represented in red, but this would be significantly reduced in a more joined up approach.

The start point for many organisations is essentially delivering the different channel options. And we know, a lot of organizations are still yet to go on the chatbot journey, and some don’t have live chat.

The aim is a more joined up approach, understanding what is failing within each channel, and having the sort of the insights and the analytics to help improve and reduce that non first contact resolution. This is a great step forward and what we should be striving to achieve.

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